Entrance Detection from Street-Level Imagery

1. A computer-implemented method comprising: accessing images of a façade of a building; extracting one or more entrance candidates from the images by detecting vertical edgelets in the images using edge detection, a vertical edgelet including an edge pixel and one or more neighboring pixels along a vertical axis; and selecting one or more true candidates from the one or more entrance candidates based on known constraints of entrances.

2. The computer-implemented method of claim 1 , further comprising: determining a frontal view of the façade using a map of the façade of the building; generating a foreground mask that masks out portions of the images outside the frontal view of the façade; and applying the foreground mask to the images.

3. The computer-implemented method of claim 2 , further comprising: determining a ground line using the map; and generating the foreground mask, the foreground mask masking out portions of the images below the ground line.

4. The computer-implemented method of claim 1 , wherein extracting one or more entrance candidates from the images further comprises: separating entrances from non-entrances using a classifier, the classifier performing automatic feature selection and entrance classification to remove non-entrances.

5. The computer-implemented method of claim 4 , wherein features used in the classifier include degree of entrance symmetry and entrance color.

6. The computer-implemented method of claim 1 , wherein extracting one or more entrance candidates from the images further comprises: generating a distribution of all detected vertical edgelets; extracting a number of top ranked local peaks from the distribution to determine one or more vertical boundaries; and determining one or more entrance candidates based on the one or more vertical boundaries.

7. The computer-implemented method of claim 6 , further comprising: detecting horizontal edgelets in the images using edge detection; generating a second distribution of all detected horizontal edgelets; extracting a number of top ranked local peaks from the second distribution to determine one or more horizontal boundaries; and selecting one or more entrance candidates, each entrance candidate having a pair of vertical boundaries within a predefined ratio of length to a horizontal boundary of the one or more horizontal boundaries.

8. The computer-implemented method of claim 1 , wherein selecting one or more true candidates from the entrance candidate further comprises: projecting the entrance candidates into multi-dimensional space to resolve conflicts based on the known physical constraints using a multi-dimensional reasoning component, the known physical constraints encoded within a multi-dimensional reasoning component.

9. A system for detecting entrances in images of structural facades, comprising: at least one processor configured to execute computer-executable instructions in a computer readable hardware storage memory, the computer-executable instructions, when executed by the processor, cause the processor to: access images of a façade of a building; extract one or more entrance candidates from the images by detecting vertical edgelets in the images using edge detection, a vertical edgelet including an edge pixel and one or more neighboring pixels along a vertical axis; and selecting one or more true candidates from the one or more entrance candidates based on known constraints of entrances.

10. The system of claim 9 , wherein the computer readable hardware storage memory comprises further computer-executable instructions, that when executed by the processor, cause the processor to: determining a frontal view of the façade using a map of the façade of the building; generating a foreground mask that masks out portions of the images outside the frontal view of the façade; and applying the foreground mask to the images.

11. The system of claim 10 , wherein the computer readable hardware storage memory comprises further computer-executable instructions, that when executed by the processor, cause the processor to: determine a ground line using the map; and generate the foreground mask, the foreground mask masking out portions of the images below the ground line.

12. The system of claim 9 , wherein the computer readable hardware storage memory comprises further computer-executable instructions for the extraction of the one or more entrance candidates from the images, that when executed by the processor, cause the processor to: separate entrances from non-entrances using a classifier, the classifier performing automatic feature selection and entrance classification to remove non-entrances.

13. The system of claim 12 , wherein features used in the classifier include degree of entrance symmetry and entrance color.

14. The system of claim 9 , wherein the computer readable hardware storage memory comprises further computer-executable instructions for the extraction of the one or more entrance candidates from the images, that when executed by the processor, cause the processor to: generate a distribution of all detected vertical edgelets; extract a number of top ranked local peaks from the distribution to determine one or more vertical boundaries; and determine one or more entrance candidates based on the one or more vertical boundaries.

15. The system of claim 14 , wherein the computer readable hardware storage memory comprises further computer-executable instructions, that when executed by the processor, cause the processor to: detect horizontal edgelets in the images using edge detection; generate a second distribution of all detected horizontal edgelets; extract a number of top ranked local peaks from the second distribution to determine one or more horizontal boundaries; and select one or more entrance candidates, each entrance candidate having a pair of vertical boundaries within a predefined ratio of length to a horizontal boundary of the one or more horizontal boundaries.

16. A computer-readable hardware storage medium comprising computer-executable instructions for detecting entrances in images of structural facades that when executed by a processor, cause the processor to: access images of a façade of a building; extract one or more entrance candidates from the images by detecting vertical edgelets in the images using edge detection, a vertical edgelet including an edge pixel and one or more neighboring pixels along a vertical axis; and select one or more true candidates from the one or more entrance candidates based on known constraints of entrances.

17. The computer-readable hardware storage medium of claim 16 , comprising further computer-executable instructions, that when executed by the processor, cause the processor to: determine a frontal view of the façade using a map of the façade of the building; generate a foreground mask that masks out portions of the images outside the frontal view of the façade; and apply the foreground mask to the images.

18. The computer-readable hardware storage medium of claim 17 , comprising further computer-executable instructions, that when executed by the processor, cause the processor to: determine a ground line using the map; and generate the foreground mask, the foreground mask masking out portions of the images below the ground line.

19. The computer-readable hardware storage medium of claim 16 , comprising further computer-executable instructions for the extraction of the one or more entrance candidates from the images, that when executed by the processor, cause the processor to: separate entrances from non-entrances using a classifier, the classifier performing automatic feature selection and entrance classification to remove non-entrances.

20. The computer-readable hardware storage medium of claim 16 , comprising further computer-executable instructions for the extraction of the one or more entrance candidates from the images, that when executed by the processor, cause the processor to: generate a distribution of all detected vertical edgelets; extract a number of top ranked local peaks from the distribution to determine one or more vertical boundaries; and determine one or more entrance candidates based on the one or more vertical boundaries.